1. Field of the Present Invention
The present invention relates to a filtering mechanization method, and more particularly to a filtering mechanization method for integration of a Global Positioning System (GPS) receiver with an Inertial Measurement Unit (IMU) to produce highly accurate, highly reliable, and mixed GPS/IMU position, velocity, and attitude measurements of a carrier at affordable cost under high dynamic environments, heavy noise environments, and long-term (long-period) operation.
2. Description of Related Arts
The major function of a navigation system is designed to produce continuous position, velocity, and attitude measurements of a carrier, such as a vehicle, under dynamic environments. The attitude measurements usually include pitch, roll, and heading angle of the carrier.
In the past decade, a low cost inertial navigation system (INS) and GPS (Global Positioning System) receiver were commonly developed to determine the positioning measurements of a vehicle at affordable cost, such as position, velocity, etc.
An INS relies on three orthogonally mounted inertial angular rate sensors and three orthogonally mounted acceleration sensors to produce three-axis angular rate and acceleration measurements. Based on the carrier acceleration and angular rate measurements, the position, velocity, and attitude measurements of a carrier are obtained by numerically solving Newton""s equations of motion. The three orthogonally mounted inertial angular rate sensors and three orthogonally mounted acceleration sensors with additional supporting mechanical structures and electronic devices are conventionally called an Inertial Measurement Unit (IMU). The conventional IMUs may be catalogued into Platform IMU and Strapdown IMU.
In the platform IMU, angular rate sensors and acceleration sensors are installed on a stabilized platform. Attitude measurements can be directly picked off from the platform structure. But attitude rate measurements cannot be directly obtained from the platform. Moreover, highly accurate feedback control loops must be designed to implement the platform IMU.
Compared with the platform IMU, in a strapdown IMU, the angular rate sensors and acceleration producers are directly strapped down to the carrier and move with the carrier. The output signals of the angular rate sensors and acceleration sensors are expressed in the carrier body frame. The attitude and attitude rate measurements can be obtained by means of a series of computations.
The INS, which uses a platform IMU, in general, is catalogued as a gimbaled inertial navigation system. The INS, which uses a strapdown IMU, in general, is catalogued as a strapdown inertial navigation system. In a gimbaled inertial navigation system, the angular rate sensors and acceleration sensors are mounted on a gimbaled platform to isolate the sensors from the rotations of the carrier so that the measurements and navigation calculations can be performed in a stabilized navigation coordinates frame. Generally, the motion of the carrier can be expressed in several navigation frames of reference, such as earth centered inertial (ECI), earth-centered earth-fixed (ECEF), and North-East-Down (NED), etc. In a strapdown inertial navigation system, the inertial sensors are rigidly mounted to the carrier body frame. In order to perform the navigation computation in the stabilized navigation frame, a coordinate frame transformation matrix is used and updated to transform the acceleration measurements from the body frame to the navigation frame.
In general, the navigation solution from the gimbaled inertial navigation system is more accurate than the one from the strapdown inertial navigation system. But, a gimbaled inertial navigation system is more complex and expensive than a strapdown inertial navigation system. The strapdown inertial navigation systems become the predominant mechanization due to their low cost and reliability.
An inertial navigation system provides the position, velocity, and attitude information of a carrier through a dead reckoning method. Inertial navigation systems, in principle, perform a self-contained operation and output continuous position, velocity, and attitude data of the carrier after initializing the starting position and initiating an alignment procedure.
In addition to the self-contained operation, other advantages of an inertial navigation system include the full navigation solution and wide bandwidth.
However, an inertial navigation system is expensive and is degraded with drift in output (position, velocity, and attitude) over an extended period of time. It means that the position and velocity errors increase with time. This error propagation characteristic is primarily caused by errors, such as, gyro drifts, accelerometer bias, misalignment, gravity disturbance, initial position and velocity errors, and scale factor errors.
Generally, the ways of improving the accuracy of inertial navigation systems include employing highly accurate inertial sensors and aiding the inertial navigation system using an external sensor. However, highly accurate inertial sensors are very expensive with big size and heavy weight.
A GPS receiver is a very ideal external source to aid an inertial navigation system. The GPS is a satellite-based, worldwide, all-weather radio positioning and timing system. The GPS system is originally designed to provide precise position, velocity, and timing information on a global common grid system to an unlimited number of adequately equipped users.
GPS receivers are designed for a user to exploit the advantages of the Global Positioning System. A conventional, single antenna GPS receiver supplies world-wide, highly accurate three dimensional position, velocity, and timing information, but not attitude information, by processing the so-called pseudo range and delta range measurements output from the code tracking loops and the carrier tracking loops in the GPS receiver, respectively. In a benign radio environment, the GPS signal propagation errors and GPS satellite errors, including the Selective Availability, serve as the bounds for positioning errors. However, the GPS signals may be intentionally or unintentionally jammed or spoofed, and the GPS receiver antenna may be obscured during carrier attitude maneuvering, and the performance degrades when the signal-to-noise ratio of the GPS signal is low and the carrier is undergoing highly dynamic maneuvers.
As both the cost and size of high performance GPS receivers are reduced in the past decade, a multiple-antenna GPS receiver was developed to provide both position and attitude solutions of a vehicle, using interferometric techniques. In principle, the attitude determination technology utilizes measurements of GPS carrier phase differences on the multiple-antenna to obtain highly accurate relative position measurements. Then, the relative position measurements are converted to the attitude solution. The advantages of this approach are long-term stability of the attitude solution and relatively low cost. However, this GPS position and attitude determination system still retains the characterization of low bandwidth which is susceptible to shading and jamming, requires at least 3 antennas configurations for a three-axis attitude solution, and requires antenna separation enough for high attitude resolution.
Because of the inherent drawbacks of a stand-alone inertial navigation system and a stand-alone GPS receiver, a stand-alone inertial navigation system or a stand-alone GPS receiver can not meet mission requirements under some constraints, such as low cost, long-term high accuracy, highly reliable, continuous high rate output, etc.
The mutual complementary characteristics of the stand-alone GPS receiver and the stand-alone inertial navigation system suggest that, in many applications, an integrated GPS/IMU system, combining the best positive properties of both systems, will provide superior accurate continuous navigation capability. This navigation capability is unattainable in either one of the two systems standing alone.
The potential benefits offered by an integrated GPS/IMU system are outlined as follows:
(1) The aiding of the GPS receiver signal-tracking loop process with inertial data allows the effective bandwidth of the loops to be reduced, resulting in an improved tracking signal in noisy and dynamic environments.
(2) An inertial navigation system not only provides navigation information when the GPS signal is lost temporarily, but also reduces the search time required to reacquire GPS signals.
(3) Inertial navigation parameter errors and inertial sensor errors can be calibrated while the GPS signal is available, so that the inertial navigation system can provide more accurate pure inertial position information after the GPS signal is lost.
(4) The GPS enables and provides on-the-fly alignment of an inertial navigation system by means of maneuvering, eliminating the static self-alignment pre-mission requirements of the stand-alone inertial navigation system.
Conventionally, a standard Kalman filtering mechanization, which uses centralized processing mechanization, is used to integrate the navigation information from a GPS receiver with that from an INS. However, the conventional method often suffers from some potential problems, such as correlated noise of the GPS receiver output, unpredicted big transient errors of the GPS velocity, level changes of the GPS receiver output errors due to change of the GPS satellite in view, and other undetected GPS failures.
Moreover, for versatile commercial applications, a low cost, low accuracy IMU is integrated with a GPS chipset. Thus, the long-term position and velocity output of the integrated GPS/IMU system heavily rely on the update of the GPS position and velocity. Therefore, it is very important that the integration process automatically exclude GPS false solutions, so that the integrated GPS/IMU system can exploit the GPS positive features, but remove the GPS negative features. The present invention is disclosed to address these problems.
A main objective of the present invention is to provide a filtering mechanization method of integrating global positioning system receiver with inertial measurement unit, wherein measurements from a GPS (Global Positioning System) receiver and an IMU (Inertial Measurement Unit) are optimally processed to achieve highly accurate and reliable mixed GPS/IMU position, velocity, and attitude information of a carrier under high dynamic, heavy jamming, and long-term operation environments. The present invention features greater flexibility to incorporate GPS failure detection/isolation requirements of the integrated GPS/IMU systems.
Another objective of the present invention is to provide a filtering mechanization method of integrating global positioning system receiver with inertial measurement unit, wherein the position and velocity data from the GPS receiver are independently filtered first in parallel with the output from the inertial navigation processing to obtain two sets of local state vector estimates, including INS navigation parameter errors and inertial sensor errors, and then the two sets of local state vector estimates are mixed to obtain one set of global state vector estimate, including the INS navigation parameter errors and inertial sensor errors, with maximal fault toleration.
Another objective of the present invention is to provide a filtering mechanization method of integrating global positioning system receiver with inertial measurement unit, wherein the local and master filtering mechanization with flexible different update rates is applied to the integration of the GPS receiver with an IMU to overcome the problem of the correlated errors of the position and velocity output from the GPS Kalman filter in conventional GPS/IMU integration approaches.
Another objective of the present invention is to provide a filtering mechanization method of integrating global positioning system receiver with inertial measurement unit, wherein the local and master filter can be incorporated to minimize the response transients when the GPS satellite constellation in view change occurs.
Another objective of the present invention is to provide a filtering mechanization method of integrating global positioning system receiver with inertial measurement unit, wherein the local and master filters can be incorporated to autonomously exclude big unpredicted GPS velocity jumps, such as the transients order of a few meters per second without any other indication.
Another objective of the present invention is to provide a filtering mechanization method of integrating global positioning system receiver with inertial measurement unit, wherein the local and master filters with a failure detection/isolation logic can detect and isolate GPS failures, especially GPS soft failures. The GPS soft failure means that failure is slowly accumulated, which are very tough to detect traditionally.
In order to accomplish the above objectives, the present invention provides a filtering mechanization method for integrating a GPS receiver carried by a carrier with an IMU carried by the carrier for producing a GPS/IMU mixed positioning data of the carrier, which comprises the steps of:
(a) receiving angular rate and acceleration measurements of the carrier from the IMU to a navigation equations processor to produce INS position, velocity, and attitude data of the carrier;
(b) sending INS velocity data from the navigation equations processor and GPS velocity data from a GPS receiver into the first local filter;
(c) producing the first local state vector estimate and the first local error covariance matrix by the first local filter;
(d) sending GPS position data of the GPS receiver and INS position data from the navigation equations processor into the second local filter;
(e) producing the second local state vector estimate and the second local error covariance matrix by the second local filter;
(f) receiving the first local state vector estimate and first local error covariance matrix and the second local state vector estimate and second local error covariance matrix by a master filter to mix the first local filter""s state vector estimate and the second filter""s state vector estimate to form optimal estimates of the global state vector and global error covariance matrix, including INS parameter errors, inertial sensor errors, and GPS correlated position and velocity error estimates, as output of the INS filter; and
(g) compensating the INS position, velocity, and attitude data output of the navigation equations processor using the optimal estimates of the INS parameter errors of the global state vector by an error remover to form the mixed GPS/IMU position, velocity, and attitude data output.